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Estimated Rating Based on Hours Played for Video Game Recommendation

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Distributed Computing and Artificial Intelligence, Special Sessions, 15th International Conference (DCAI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 801))

Abstract

This work presents a method to estimate ratings for video games based on the user’s playing hours. Based on these ratings, through collaborative filtering techniques, it is possible to make recommendations for video games without taking into account their popularity, solving the problem of long tail. The item-based k-NN algorithms and SVD++ are the ones that obtains the best results with the proposed estimation method, improving the original one and obtaining similar results in the rest of cases.

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Notes

  1. 1.

    http://steamspy.com/year/.

  2. 2.

    http://store.steampowered.com/.

  3. 3.

    https://www.kaggle.com/tamber/steam-video-games.

  4. 4.

    https://www.kaggle.com.

References

  1. Hu, Y., Koren, Y., Volinsky, C.: Collaborative filtering for implicit feedback datasets. In: 2008 Eighth IEEE International Conference on Data Mining, pp. 263–272. IEEE, December 2008. http://ieeexplore.ieee.org/document/4781121/

  2. Koren, Y., Research, Y.: Factor in the neighbors: scalable and accurate collaborative filtering. ACM Trans. Knowl. Discov. Data 4(1) (2010). http://courses.ischool.berkeley.edu/i290-dm/s11/SECURE/a1-koren.pdf

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  3. Koren, Y.: Factorization meets the neighborhood. In: Proceeding of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD 2008, p. 426. ACM Press, New York (2008). http://dl.acm.org/citation.cfm?doid=1401890.1401944

  4. Lemire, D., Maclachlan, A.: Slope One Predictors for Online Rating-Based Collaborative Filtering, February 2007. http://arxiv.org/abs/cs/0702144

  5. Pacula, M.: A matrix factorization algorithm for music recommendation using implicit user feedback (2009)

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Acknowledgements

This work was supported by the Spanish Ministry, Ministerio de Economía y Competitividad and FEDER funds. Project. SURF: Intelligent System for integrated and sustainable management of urban fleets TIN2015-65515-C4-3-R.

Author information

Authors and Affiliations

  1. BISITE Digital Innovation Hub, University of Salamanca, Edificio Multiusos I+D+i, 37007, Salamanca, Spain

    Javier Pérez-Marcos

  2. Departamento de Informática y Automática, University of Salamanca, Salamanca, Spain

    Diego Sánchez-Moreno, Vivian López Batista & María Dolores Muñoz

Authors
  1. Javier Pérez-Marcos
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  2. Diego Sánchez-Moreno
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  3. Vivian López Batista
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  4. María Dolores Muñoz
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Corresponding author

Correspondence to Javier Pérez-Marcos .

Editor information

Editors and Affiliations

  1. BISITE Digital Innovation Hub, University of Salamanca, Salamanca, Spain

    Sara Rodríguez

  2. BISITE Digital Innovation Hub, University of Salamanca, Salamanca, Spain

    Javier Prieto

  3. GECAD - Instituto Superior de Engenharia, Porto, Portugal

    Pedro Faria

  4. Department of Computer Science and Production Management, University of Zielona Góra, Zielona Góra, Poland

    Sławomir Kłos

  5. Computing Science and Artificial Intelligence, Rey Juan Carlos University, Móstoles, Madrid, Spain

    Alberto Fernández

  6. Basque Center for Applied Mathematics, Bilbao, Spain

    Santiago Mazuelas

  7. Basque Center for Applied Mathematics, Universidad de Alcalá, Alcalá de Henares, Spain

    M. Dolores Jiménez-López

  8. Departamento de Informática y Automática, University of Salamanca, Salamanca, Spain

    María N. Moreno

  9. Departamento de Sistemas Informáticos, University of Castilla-La Mancha, Albacete, Spain

    Elena M. Navarro

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Cite this paper

Pérez-Marcos, J., Sánchez-Moreno, D., Batista, V.L., Muñoz, M.D. (2019). Estimated Rating Based on Hours Played for Video Game Recommendation. In: Rodríguez, S., et al. Distributed Computing and Artificial Intelligence, Special Sessions, 15th International Conference. DCAI 2018. Advances in Intelligent Systems and Computing, vol 801. Springer, Cham. https://doi.org/10.1007/978-3-319-99608-0_34

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